Hierarchical encoding methods with spatial scalability are known. Scalability represents the ability to stagger information to make it decodable at multiple resolution and/or quality levels. More specifically, a data stream generated by this type of encoding method is divided into several layers, in particular a basic layer and one or more enhancement layers. These methods are used in particular to adapt a single data stream to variable transport conditions (bandwidth, error ratios, etc.), and to the expectations of the customers and the varying capabilities of their receivers (CPU, specifications of the display device, etc.). In the particular case of spatial scalability, the part of the data stream corresponding to low resolution pictures of the sequence can be decoded independently of the part of the data stream corresponding to the high resolution pictures. On the other hand, the part of the data stream corresponding to high resolution pictures of the sequence can be decoded only from the part of the data stream corresponding to the low resolution pictures.
Hierarchical encoding with spatial scalability makes it possible to encode a first data part called basic layer, relative to the low resolution pictures and, from this basic layer, a second data part called enhancement layer, relative to the high resolution pictures. Normally, each macroblock of the high resolution picture is temporally predicted according to a conventional prediction mode (for example, bidirectional prediction mode, direct mode, forward prediction mode, etc.) or indeed is predicted according to an inter-layer prediction mode. In this latter case, motion data (for example, a partitioning of the macroblock into blocks, possibly including motion vectors and reference picture indices) and, where appropriate, texture data associated with a block of pixels of the high resolution picture, is deduced or inherited from the motion data, or respectively texture data, is associated with blocks of pixels of a low resolution picture. However, the known methods do not allow such predictors to be generated in the case where the low resolution sequence is progressive and the high resolution sequence is interlaced.